Effects of Replacing Fishmeal with American Cockroach Residue on the Growth Performance, Metabolism, Intestinal Morphology, and Antioxidant Capacity of Juvenile <i>Cyprinus carpio<... by Xiaofang Zou, Chenggui Zhang, Bingyan Guo, Yu Cao, Yongshou Yang, Peiyun Xiao, Xiaowen Long

“…Juvenile <i>Cyprinus carpio</i> (initial body weight approximately 74 g) were randomly assigned to these diets for a 10-week feeding trial. …”
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The value of machine learning based on spectral CT quantitative parameters in the distinguishing benign from malignant thyroid micro-nodules by Zuhua Song, Qian Liu, Jie Huang, Dan Zhang, Jiayi Yu, Bi Zhou, Jiang Ma, Ya Zou, Yuwei Chen, Zhuoyue Tang

“…To explore the application value of various machine learning (ML) algorithms based on dual-layer spectral computed tomography (DLCT) quantitative parameters in distinguishing benign from malignant thyroid micro-nodules. …”
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Novel multilayer meniscal scaffold provides biomechanical and histological results comparable to polyurethane scaffolds: An 8 week rabbit study by Nihat Demirhan Demirkıran, Hasan Havıtçıoğlu, Aylin Ziylan, Ülker Cankurt, Buğra Hüsemoğlu

“…Methods: Sixteen NewZealand rabbits were randomly divided into three groups. A reproducible 1.5-mm cylindrical defect was created in the avascular zone of the anterior horn of the medial meniscus bilaterally. …”
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Early Parenting Intervention – Biobehavioral Outcomes in infants with Neurodevelopmental Disabilities (EPI-BOND): study protocol for an Italian multicentre randomised controlled tr... by Rosario Montirosso, Elisa Rosa, Roberto Giorda, Elisa Fazzi, Simona Orcesi, Anna Cavallini, Renato Borgatti, Camilla Caporali, Linda Gasparini, Serena Micheletti, Cecilia Naboni, Elisa Scarano, Eleonora Visintin

“…The present multi-centric and longitudinal randomised controlled trial aims to assess if and to which extent early VFI could benefit both infants and mothers in terms of behavioural outcomes as well as neuroendocrine and epigenetic regulation.Methods and analysis Dyads will be randomly assigned to the video-feedback Intervention Group or Control Group (‘dummy’ intervention: telephone calls). …”
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Effects of Agrochemicals on Soil Bio-Physico-Chemical Properties in Potato Production Systems in the Highlands of South Western Uganda. by Twebaze, Jeniffer

“…It was observed that the majority of the macrofauna existed in the topsoil layer at a depth of 0-10 cm other than the 10-30 cm. …”
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Effects of tannic acid on growth performance, intestinal health, and tolerance in broiler chickens by Huiping Xu, Lu Gong, Xiaodan Zhang, Zhenyi Li, Jianyang Fu, Zengpeng Lv, Yuming Guo

“…Experiment 2 was performed to evaluate the tolerance of tannic acid; 416 broilers were randomly divided into control (CTR), 0.075 % tannic acid (TA), 0.375 % tannic acid (5TA), and 0.75 % tannic acid (10TA) groups. …”
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Stratified allocation method for water injection based on machine learning: A case study of the Bohai A oil and gas field by Changlong Liu, Pingli Liu, Qiang Wang, Lu Zhang, Zechao Huang, Yuande Xu, Shaojiu Jiang, Le Zhang, Changxiao Cao

“…Third, 300 neurons and three hidden layers were used in the optimized neural network. …”
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MSCPUnet: A multi-task neural network for plot-level crop classification in complex agricultural areas by Kedi Fang, Shengwei Zhang, Yongting Han, Lin Yang, Meng Luo, Lu Liu, Qian Zhang, Bo Wang

“…MSCPUnet is based on the Unet model and enhances performance through the incorporation of attention mechanisms, multi-scale pooling layers, and a multi-task learning approach for parallel processing. …”
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A comparative study of different kinematic wake models within metaheuristics for efficient wind farm layout optimization by Antonio J. Romero-Barrera, David Casillas-Pérez, Laura Cornejo-Bueno, Jorge Pérez-Aracil, Alvaro Paricio-Garcia, Miguel A. Lopez-Carmona, Juan Blanco-Sancho, Sujan Ghimire, Ravinesh C. Deo, Antonio J. Caamaño, Sancho Salcedo-Sanz

“…Results show 10-15% efficiency improvements compared to random population initializations, with larger terrains favoring ensemble-based optimization, while denser layouts benefit from evolutionary approaches. …”
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Integrating Gene Expression Data into Single-Step Method (ssBLUP) Improves Genomic Prediction Accuracy for Complex Traits of Duroc × Erhualian F₂ Pig Population by Fangjun Xu, Zhaoxuan Che, Jiakun Qiao, Pingping Han, Na Miao, Xiangyu Dai, Yuhua Fu, Xinyun Li, Mengjin Zhu

“…Generally, the gene expression data are integrated into multiple random effect models as independent data layers or used to replace genotype data for genomic prediction. …”
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Modelling and simulation of the block pouring construction system considering spatial–temporal conflict of construction machinery in arch dams by Zhipeng Liang, Jiayao Peng, Chunju Zhao, Huawei Zhou, Dongfeng Li, Yihong Zhou, Quan Liu, Xiaodong Li, Cheng Zhang, Fang Wang

“…The outbreak of mechanical spatial–temporal conflict in the construction process of the arch dam pouring block is random and uncertain. Scientific simulation and preview of the pouring construction process and analysis of the level, time, and influence degree of the outbreak of spatial–temporal conflict are significant means to optimize the construction organization and management. …”
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Quantitative Analysis of Structural Parameters Importance of Helical Temperature Microfiber Sensor by Artificial Neural Network by Juan Liu, Minghui Chen, Hang Yu, Jinjin Han, Hongyi Jia, Zhili Lin, Zhijun Wu, Jixiong Pu, Xining Zhang, Hao Dai

“…Based on the BPNN with precise prediction, the backward stepwise elimination and the holdback input randomization methods are used to quantitatively discuss the influence of the structural parameters on the output intensity of the HMF. …”
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Microstructure-dependent phosphating film formation and its corrosion behavior in AZ91 Mg alloy: Effect of extrusion temperature by Haolong Bai, Junlei Zhang, Qiuyue Shi, Xiang Chen, Xuwen Yuan, Shengbo Hu, Chao He, Qi Zhao, Shuping Tan, Yifu Shen, Guangsheng Huang

“…Conversely, high-temperature extrusion (450 °C) induced grain coarsening (14.7 μm) and texture randomization (27.2.0 % basal-oriented grains), which led to a relatively thin and less uniform phosphate film with increased microcracks, thereby compromising the corrosion performance. …”
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Expanding structural insights into DNA packaging apparatus and endolysin LysSA05 function of Epsilon15 bacteriophage by Muhammad Saleem Iqbal Khan, Ju Wu, Shenlin Ji, Demeng Tan, Bingrui Sui, Shanshan Peng, Jinbiao Zhan, Jiajun Yin

“…This approach resolved the full asymmetric architecture of ϵ15, revealing a detailed internal nucleic acid organization with at least eight concentric layers radially and approximately 28 axially compacted layers within the capsid. …”
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Prediction of hydrogen production in proton exchange membrane water electrolysis via neural networks by Muhammad Tawalbeh, Ibrahim Shomope, Amani Al-Othman, Hussam Alshraideh

“…The optimized ANN configuration features an architecture with 7 input nodes, two hidden layers of 64 neurons each, and a single output node. …”
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Cost-Efficient RSSI-Based Indoor Proximity Positioning, for Large/Complex Museum Exhibition Spaces by Panos I. Philippopoulos, Kostas N. Koutrakis, Efstathios D. Tsafaras, Evangelia G. Papadopoulou, Dimitrios Sigalas, Nikolaos D. Tselikas, Stefanos Ougiaroglou, Costas Vassilakis

“…Pilot implementation decisions and methods adopted at all layers of the VTT architecture followed the overall concept of simplicity, availability, and cost-efficiency, providing a maximum infrastructure cost of 8 Euro per m² covered. …”
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Machine learning prediction of permeability distribution in the X field Malay Basin using elastic properties by Zaky Ahmad Riyadi, John Oluwadamilola Olutoki, Maman Hermana, Abdul Halim Abdul Latif, Ida Bagus Suananda Yogi, Said Jadid A. Kadir

“…Several ensemble-based models, including Extreme Gradient Boosting (XGBoost), Light Gradient Boosting (LightBoost), Categorical Gradient Boosting (CatBoost), Bagging Regressor, Random Forest and Stacking, were evaluated for predictive performance, along with Multi-Layered Perceptron Neural Network algorithms. …”
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MC-ASFF-ShipYOLO: Improved Algorithm for Small-Target and Multi-Scale Ship Detection for Synthetic Aperture Radar (SAR) Images by Yubin Xu, Haiyan Pan, Lingqun Wang, Ran Zou

“…Two key innovations distinguish our approach: (1) We introduce a Monte Carlo Attention (MCAttn) module into the backbone network that employs random sampling pooling operations to generate attention maps for feature map weighting, enhancing focus on small targets and improving their detection performance. (2) We add Adaptively Spatial Feature Fusion (ASFF) modules to the detection head that adaptively learn spatial fusion weights across feature layers and perform dynamic feature fusion, ensuring consistent ship representations across scales and mitigating feature conflicts, thereby enhancing multi-scale detection capability. …”
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Assessment of Machine Learning Models for Predicting Aboveground Biomass in the Indian Subcontinent by S. Mamgain, B. Ghale, H. C. Karnatak, A. Roy

“…This study evaluates three machine learning models&mdash;Random Forest (RF), Gradient Tree Boosting (GTB), &amp; Classification and Regression Trees (CART)&mdash;for predicting AGB across the subcontinent. …”
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the effect of knowledge management on organizational effectiveness with the mediating role of employees&#039; spiritual intelligence (case study: the field of police crime preventi... by Abdulrahman Mirzakhani, Sayyad Darvishi

“…Based on stratified and simple random sampling, the sample size included 103 participants. …”
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